Create a Derived Metric Using the Metric Function Editor

This topic is focused on creating a derived metric within a dashboard. (Derived metrics created within a dashboard are saved within the dashboard and therefore cannot be used outside of it.)

• If you arrived here while creating a new stand-alone metric, see Create a Stand-Alone Metric. A stand-alone metric is saved as a separate object that can be placed on multiple reports and dashboards; those reports can be used as datasets on multiple dashboards and documents.

• If you arrived here while creating a derived metric within a report, see Create Derived Metrics in Reports.

• If you arrived here while creating a derived metric within a document, see Create a Derived Metric from Scratch in a Document.

You can create new metrics, called derived metrics, based on attributes and metrics that have already been added to a dashboard.

You can create a new metric by subtracting the values of one metric from the values of another metric, such as Revenue Forecast - Revenue. You can rank a metric's value from least to greatest, or display metric values as percentages of an accumulated total.

Create a Derived Metric Using the Metric Function Editor

1. Open the dashboard you want to modify.

2. In the Datasets panel, right-click the metric to use to create a derived metric and choose Create Metric.

   • To add the derived metric immediately to a specific visualization, in the Editor panel for that visualization, right-click a metric and choose Create Metric.

3. Type a name for the metric in the Metric Name field.
4. Type a description of your derived metric in the Description field.

5. To locate a function, enter its name in Search. You can also browse for a function by selecting a function category (that is, Basic Functions, String Functions, and so on) from the drop-down list.

   • To view a description of a function, click it in the left pane; its description displays at the bottom of the interface. Click Details to view more information about the function and its arguments in the Functions Reference . See Add Conditional Calculations to a Derived Metric Using the If and Case Functions for more information about the If and Case functions.

6. Click a function to add it to the derived metric definition in the right pane.
   • If you select an aggregation function (that is, a grouping function), such as First, Maximum, or Sum, the Level and Filter fields display under Function Parameters.
     1. The function applies to the metric you selected in the Datasets panel. From the drop-down list, you can select a different metric or an attribute element.
     2. Define function parameters, such as whether to use all values in the calculation or calculate using only unique values. Click Function Parameters, select the appropriate options to define the parameters, and click OK.

     3. The function is calculated at the level of the attributes on the visualization on which the metric is placed, by default. You can specify the attributes to use in the metric calculation, regardless of what is contained on any visualization that the metric is placed on. To change the level, select an attribute from the Level drop-down list. You can also add multiple attributes. For more details on level derived metrics, including how to allow them to adapt to visualizations or calculate values for the attribute level only, and how to use dynamic/location-based levels, see Create a Level Metric Within a Dashboard.

        For example, if a visualization contains Region and Category, by default the metric calculates regional and category values on that visualization. If you select Region as the level, the metric calculates the regional revenue values on that visualization; it does not include a breakdown by Category. This allows you to compare revenue across regions.

     4. You can add advanced filtering to your metric. Click Add Filter to open the New Qualification dialog. See Introduction to Advanced Filtering for more information.

     5. If the Sort By field appears, select options for sorting the data.
   • If you select a non-aggregation function, such as data mining, date, OLAP, and ranking functions, options appear that allow you to define the input values (that is, arguments) for the function, as well as any parameters that determine the behavior of the function. Enter the appropriate options.
7. Click Save.

The derived metric is displayed on the Datasets panel with the derived metric icon .

Aggregation and subtotal behavior is automatically determined by default. You can change that behavior to specify whether the derived metric is calculated using the whole dataset or calculated using the data in the visualization that it is placed on. See Change the Aggregation and Subtotal Behavior for a Derived Metric for more information.

Related Topics

Metrics in Dashboards

Derived Metrics: Metrics Based on Existing Objects

Create a Derived Metric On a Grid Using a Shortcut

Create a Derived Metric by Combining Two Metrics with an Operator

Create a Derived Metric by Combining Multiple Metrics

Create a Derived Metric by Selecting the Aggregation Function

Create a Derived Metric from an Attribute

Create a Derived Metric from Scratch Using the Metric Formula Editor

Change the Aggregation and Subtotal Behavior for a Derived Metric

Provide Statistical Analysis from R Analytics

Edit Derived Metrics from the Dashboard

Rename Derived Metrics from the Dashboard

Delete Derived Metrics from the Dashboard